Fuzzy time series for projecting school enrolment in Malaysia / Nor Hayati Shafii … [et al.]

There are a variety of approaches to the problem of predicting educational enrolment. However, none of them can be used when the historical data are linguistic values. Fuzzy time series is an efficient and effective tool to deal with such problems. In this paper, the forecast of the enrolment of p...

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Main Authors: Shafii, Nor Hayati, Alias, Rohana, Shamsudin, Siti Rohani, Mohd Nasir, Diana Sirmayunie
Format: Article
Language:en
Published: UiTM Cawangan Perlis 2021
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/47082/1/47082.pdf
https://ir.uitm.edu.my/id/eprint/47082/
https://crinn.conferencehunter.com/
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author Shafii, Nor Hayati
Alias, Rohana
Shamsudin, Siti Rohani
Mohd Nasir, Diana Sirmayunie
author_facet Shafii, Nor Hayati
Alias, Rohana
Shamsudin, Siti Rohani
Mohd Nasir, Diana Sirmayunie
author_sort Shafii, Nor Hayati
building Tun Abdul Razak Library
collection Institutional Repository
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
continent Asia
country Malaysia
description There are a variety of approaches to the problem of predicting educational enrolment. However, none of them can be used when the historical data are linguistic values. Fuzzy time series is an efficient and effective tool to deal with such problems. In this paper, the forecast of the enrolment of pre-primary, primary, secondary, and tertiary schools in Malaysia is carried out using fuzzy time series approaches. A fuzzy time series model is developed using historical dataset collected from the United Nations Educational, Scientific, and Cultural Organization (UNESCO) from the year 1981 to 2018. A complete procedure is proposed which includes: fuzzifying the historical dataset, developing a fuzzy time series model, and calculating and interpreting the outputs. The accuracy of the model are also examined to evaluate how good the developed forecasting model is. It is tested based on the value of the mean squared error (MSE), Mean Absolute Percent Error (MAPE) and Mean Absolute Deviation (MAD). The lower the value of error measure, the higher the accuracy of the model. The result shows that fuzzy time series model developed for primary school enrollments is the most accurate with the lowest error measure, with the MSE value being 0.38, MAPE 0.43 and MAD 0.43 respectively.
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spelling my.uitm.ir-470822021-06-08T14:38:55Z https://ir.uitm.edu.my/id/eprint/47082/ Fuzzy time series for projecting school enrolment in Malaysia / Nor Hayati Shafii … [et al.] jcrinn Shafii, Nor Hayati Alias, Rohana Shamsudin, Siti Rohani Mohd Nasir, Diana Sirmayunie Fuzzy arithmetic Fuzzy logic There are a variety of approaches to the problem of predicting educational enrolment. However, none of them can be used when the historical data are linguistic values. Fuzzy time series is an efficient and effective tool to deal with such problems. In this paper, the forecast of the enrolment of pre-primary, primary, secondary, and tertiary schools in Malaysia is carried out using fuzzy time series approaches. A fuzzy time series model is developed using historical dataset collected from the United Nations Educational, Scientific, and Cultural Organization (UNESCO) from the year 1981 to 2018. A complete procedure is proposed which includes: fuzzifying the historical dataset, developing a fuzzy time series model, and calculating and interpreting the outputs. The accuracy of the model are also examined to evaluate how good the developed forecasting model is. It is tested based on the value of the mean squared error (MSE), Mean Absolute Percent Error (MAPE) and Mean Absolute Deviation (MAD). The lower the value of error measure, the higher the accuracy of the model. The result shows that fuzzy time series model developed for primary school enrollments is the most accurate with the lowest error measure, with the MSE value being 0.38, MAPE 0.43 and MAD 0.43 respectively. UiTM Cawangan Perlis 2021-03 Article PeerReviewed text en https://ir.uitm.edu.my/id/eprint/47082/1/47082.pdf Fuzzy time series for projecting school enrolment in Malaysia / Nor Hayati Shafii … [et al.]. (2021) Journal of Computing Research and Innovation (JCRINN) <https://ir.uitm.edu.my/view/publication/Journal_of_Computing_Research_and_Innovation_=28JCRINN=29/>, 6 (1). pp. 11-21. ISSN 2600-8793 https://crinn.conferencehunter.com/
spellingShingle Fuzzy arithmetic
Fuzzy logic
Shafii, Nor Hayati
Alias, Rohana
Shamsudin, Siti Rohani
Mohd Nasir, Diana Sirmayunie
Fuzzy time series for projecting school enrolment in Malaysia / Nor Hayati Shafii … [et al.]
title Fuzzy time series for projecting school enrolment in Malaysia / Nor Hayati Shafii … [et al.]
title_full Fuzzy time series for projecting school enrolment in Malaysia / Nor Hayati Shafii … [et al.]
title_fullStr Fuzzy time series for projecting school enrolment in Malaysia / Nor Hayati Shafii … [et al.]
title_full_unstemmed Fuzzy time series for projecting school enrolment in Malaysia / Nor Hayati Shafii … [et al.]
title_short Fuzzy time series for projecting school enrolment in Malaysia / Nor Hayati Shafii … [et al.]
title_sort fuzzy time series for projecting school enrolment in malaysia / nor hayati shafii … [et al.]
topic Fuzzy arithmetic
Fuzzy logic
url https://ir.uitm.edu.my/id/eprint/47082/1/47082.pdf
https://ir.uitm.edu.my/id/eprint/47082/
https://crinn.conferencehunter.com/
url_provider http://ir.uitm.edu.my/